TY - CONF T1 - 2D és 3D bináris objektumok lineáris deformáció-becslésének numerikus megoldási lehetőségei T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 Y1 - 2013 A1 - Attila Tanacs A1 - Joakim Lindblad A1 - Nataša Sladoje A1 - Zoltan Kato ED - László Czúni JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2013 PB - NJSZT-KÉPAF CY - Veszprém ER - TY - CONF T1 - 3D objektumok lineáris deformációinak becslése T2 - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 Y1 - 2011 A1 - Attila Tanacs A1 - Joakim Lindblad A1 - Nataša Sladoje A1 - Zoltan Kato ED - Zoltan Kato ED - Kálmán Palágyi JF - A Képfeldolgozók és Alakfelismerők Társaságának konferenciája - KÉPAF 2011 PB - NJSZT CY - Szeged ER - TY - CHAP T1 - Estimation of linear deformations of 3D objects T2 - IEEE International Conference on Image Processing (ICIP) Y1 - 2010 A1 - Attila Tanacs A1 - Joakim Lindblad A1 - Nataša Sladoje A1 - Zoltan Kato AB -

We propose a registration method to find affine transformations between 3D objects by constructing and solving an overdetermined system of polynomial equations. We utilize voxel coverage information for more precise object boundary description. An iterative solution enables us to easily adjust the method to recover e.g. rigid-body and similarity transformations. Synthetic tests show the advantage of the voxel coverage representation, and reveal the robustness properties of our method against different types of segmentation errors. The method is tested on a real medical CT volume. © 2010 IEEE.

JF - IEEE International Conference on Image Processing (ICIP) PB - IEEE CY - Hong Kong, Hong Kong N1 - UT: 000287728000038ScopusID: 78651064516doi: 10.1109/ICIP.2010.5650932 ER - TY - CHAP T1 - Recovering affine deformations of fuzzy shapes T2 - Image Analysis Y1 - 2009 A1 - Attila Tanacs A1 - Csaba Domokos A1 - Nataša Sladoje A1 - Joakim Lindblad A1 - Zoltan Kato ED - Arnt-Borre Salberg ED - Jon Yngve Hardeberg ED - Robert Jenssen AB -

Fuzzy sets and fuzzy techniques are attracting increasing attention nowadays in the field of image processing and analysis. It has been shown that the information preserved by using fuzzy representation based on area coverage may be successfully utilized to improve precision and accuracy of several shape descriptors; geometric moments of a shape are among them. We propose to extend an existing binary shape matching method to take advantage of fuzzy object representation. The result of a synthetic test show that fuzzy representation yields smaller registration errors in average. A segmentation method is also presented to generate fuzzy segmentations of real images. The applicability of the proposed methods is demonstrated on real X-ray images of hip replacement implants. © 2009 Springer Berlin Heidelberg.

JF - Image Analysis T3 - Lecture Notes in Computer Science PB - Springer-Verlag CY - Oslo, Norway N1 - UT: 000268661000075ScopusID: 70350676212doi: 10.1007/978-3-642-02230-2_75 JO - LNCS ER -